Risk of sustained SARS-CoV-2 transmission in Queensland, Australia

We used an agent-based model Covasim to assess the risk of sustained community transmission of SARSCoV-2/COVID-19 in Queensland (Australia) in the presence of high-transmission variants of the virus. The model was calibrated using the demographics, policies, and interventions implemented in the state. Then, using the calibrated model, we simulated possible epidemic trajectories that could eventuate due to leakage of infected cases with high-transmission variants, during a period without recorded cases of locally acquired infections, known in Australian settings as “zero community transmission”. We also examined how the threat of new variants reduces given a range of vaccination levels. Specifically, the model calibration covered the first-wave period from early March 2020 to May 2020. Predicted epidemic trajectories were simulated from early February 2021 to late March 2021. Our simulations showed that one infected agent with the ancestral (A.2.2) variant has a 14% chance of crossing a threshold of sustained community transmission (SCT) (i.e., > 5 infections per day, more than 3 days in a row), assuming no change in the prevailing preventative and counteracting policies. However, one agent carrying the alpha (B.1.1.7) variant has a 43% chance of crossing the same threshold; a threefold increase with respect to the ancestral strain; while, one agent carrying the delta (B.1.617.2) variant has a 60% chance of the same threshold, a fourfold increase with respect to the ancestral strain. The delta variant is 50% more likely to trigger SCT than the alpha variant. Doubling the average number of daily tests from ∼ 6,000 to 12,000 results in a decrease of this SCT probability from 43 to 33% for the alpha variant. However, if the delta variant is circulating we would need an average of 100,000 daily tests to achieve a similar decrease in SCT risk. Further, achieving a full-vaccination coverage of 70% of the adult population, with a vaccine with 70% effectiveness against infection, would decrease the probability of SCT from a single seed of alpha from 43 to 20%, on par with the ancestral strain in a naive population. In contrast, for the same vaccine coverage and same effectiveness, the probability of SCT from a single seed of delta would decrease from 62 to 48%, a risk slightly above the alpha variant in a naive population. Our results demonstrate that the introduction of even a small number of people infected with high-transmission variants dramatically increases the probability of sustained community transmission in Queensland. Until very high vaccine coverage is achieved, a swift implementation of policies and interventions, together with high quarantine adherence rates, will be required to minimise the probability of sustained community transmission.


Appendix A. Supplementary Tables
Supplementary Table S1 summarizes the references for the most relevant categories of parameters. Supplementary Figure S1: Policy-based government interventions are incorporated in the model as changes in the transmissibility of each layer. In each horizontal bar, grey portions indicate the reference level transmissibility (equal to 1). Blue portions indicate the current policies have the effect of reducing the layer's transmissibility. The darker the shade of blue, the lower the effective transmissibility in that layer. Red portions indicate that the transmissibility in that layer (here, only the home layer) is larger than baseline levels because people spend more time or are in close proximity with contacts within the layer. These changes in transmissibility were approximated by looking at the changes of policies described in multiple sources [19][20][21].
Supplementary Figure S2: Policies incorporated in the model. The colours denote four policy categories: semi-permanent public health recommendations (orange); restriction policies that reduce the spread by restricting activities of the general population (red); policies that seek to counteract the spread, such as increased testing or checking people are respecting home-quarantine (light green); and relaxation polices (green).
Supplementary Figure  In scenarios with the ancestral variant, for a cluster size of 3, Q&I leakage has a moderate effect on increasing probability of SCT from 42% (low leakage) to 52% (high leakage). However, this effect is masked in the case of the highly transmissible variants. That is, for moderate to large cluster sizes (> 7 seeded infections), community transmission is ongoing by the time the infected agents are detected and isolated, and their contacts traced and quarantined. This does not mean that Q&I interventions are not necessary but, put simply, if testing is limited, they may not be sufficient to stop SCT triggered by a small cluster of agents infected with a high-transmission variant. However, low Q&I leakage will have a crucial effect on slowing down the spread that could lead to an outbreak.
Supplementary Figure S5: Probability of detecting regimes with sustained community transmission (DSCT). A, C and E: Scenarios with cluster-seeded infections and ancestral, alpha and delta variants, respectively. B, D, F: Scenarios with Poisson-seeded infections and ancestral, alpha and delta variants, respectively. Colours and numbers represent percentage (%) probabilities calculated with respect to an ensemble of 1000 runs for each parameter set.
Supplementary Figure S6: Probability of detecting sustained community transmission (DSCT) for multiple cluster sizes of the highly transmissible variants. The dark grey line represents DSCT probabilities for ancestral and ∼ 6000 daily tests. Supplementary Figure S7: Probabilities of SCT for multiple combinations of variant and vaccine coverage, for a vaccine with 90% effectiveness against transmission. The black, dark red and dark blue lines represent SCT probabilities for delta, alpha, and ancestral respectively, assuming ∼ 6000 daily tests, and no vaccination. Solid lines are SCT probabilities as a function of vaccination coverage, that is the percentage of the adult population that has been fully vaccinated (also known as vaccine coverage). Red line: 50% vaccinated and delta; light red line 70% vaccinated and delta; light blue line 50% vaccinated and alpha; and, blue line 70% vaccinated and alpha. In the scenarios with vaccination, the cluster size represents the number of infections seeded on the first day of the simulated period. All cases have a low Q&I leakage (<10%).